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1

Subramaniyan, Mahadevan, Vijayakumar Subramaniyan, and Arulmozhi Praveenkumar. "Phytochemical Analysis and Antimicrobial Activities of Atalantia monophylla (L) Correa and Atalantia racemosa Wight and Arn." Current Bioactive Compounds 15, no. 4 (July 4, 2019): 427–36. http://dx.doi.org/10.2174/1573407214666180521105026.

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Background: Infectious diseases are major leading cause of death in all parts of the world, because of the appearance of new multi drug resistant microbes. Therefore, the discovery of potential drug for effective treatment will help the slaughter of the microbes. The aim of the present study is to evaluate the presence of photochemical and antimicrobial activities of various crude extracts of leaves, fruits and root bark of Atalantia monophylla and Atalantia racemosa against human pathogens by using well diffusion method. Methods: Antimicrobial properties of the various extracts of Atalantia monophylla and Atalantia racemosa were studied against some human pathogenic microbes such as Gram-positive Bacteria, (Bacillus subtilis, Bacillus cereus, Staphylococcus aureus) Gram-negative Bacteria (Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli) and human opportunistic fungal pathogens (Candida albicans and Aspergillus niger). All the extracts were comparable with standard drugs (Ciprofloxacin, Gentamicin, Nystatin. and Amphotericin B). Minimum inhibitory concentration (MIC), minimum bactericidal /fungicidal concentration (MBC/MFC) values were determined through a microdilution method. The phytochemical analysis of these plant extracts were carried out using standard mthods. Results: Methanolic leaf extract of A. monophylla has showed excellent antimicrobial activity against S. aureus (40mm). As well, the A. racemosa methanolic leaf extract shows notable inhibitory activity against S. aureus (38mm). At the same time, the least inhibition was observed in aqueous extract of A. monophylla against E.coli (9mm). The MIC ranged from 0.78 µg/mL to 50 µg/mL and MBC/MFC 1.56 to 50 µg/mL were recorded. Phytochemical analysis of alkaloids, steroids, saponins, flavonoids, tannins, terpenoids, phenolics and cardiae glycoside were recorded in various extracts of A. monophylla and A. racemosa respectively. Flavonoids, phenolics and cardiac glycoside were present only in methonalic leaf extract of A. monophylla. Conclusion: The result of this study concluded that methanolic leaf extract has possessed novel compounds with significant antimicrobial properties. Hence, we recommend this plant for further studies on the isolation and characterization of that lead antimicrobial potential molecule.
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2

Navarro-Lopez, Francisco. "Cardiac Diseases." Clinical Science 90, no. 3 (March 1, 1996): 156–58. http://dx.doi.org/10.1042/cs0900156.

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3

Sharma, Richa, and Shailendra Narayan Singh. "An Efficient Hybrid Classifier for Prognosing Cardiac Disease." Webology 19, no. 1 (January 20, 2022): 5028–46. http://dx.doi.org/10.14704/web/v19i1/web19338.

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Machine learning (ML) is a powerful tool which empowers the practitioners for predictions upon any existing or real- time data. Here, the Machine first understands the valuable patterns from the dataset and then uses that information to make predictions on the unknown data. Further, classification is the commonly used machine learning approach (ML-Approach) to make such predictions. The objective of this work aims to design and development of an ensemble classifier for prognosing cardiovascular disease (heart disease). The developed classifier integrates Support Vector Machine (SVM), K–Nearest Neighbor (K-NN), and Weighted K-NN. The applicability of ensemble classifier is evaluated on the Cleveland Heart disease dataset. Some other classifiers such as Logistic Regression (LR), Sequential Minimal Optimization (SMO), K-NN+Weighted K-NN are also implemented on the same dataset to make the performance analysis. The results of this study depict the significant improvement in the Sensitivity and Specificity parameter.
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4

Cocco, Giuseppe. "Geriatric Cardiac Diseases." OBM Geriatrics 4, no. 2 (April 1, 2020): 1–3. http://dx.doi.org/10.21926/obm.geriatr.2002112.

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5

Ekpe EE and Anyanwu CH. "Accuracy of trans-thoracic echocardiography as a pericardial diseases diagnostic tool." Ibom Medical Journal 1, no. 1 (August 1, 2006): 1–4. http://dx.doi.org/10.61386/imj.v1i1.1.

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SummaryA prospective comparison of pre-operative trans-thoracic echocardiographic findings with intra-operative findings of 17 patients operated on for pericardial diseases showed excellent correlation for pericardial calcification and adhesion, and for myo-cardial atrophy, and good correlation for pericardial thickening, constriction and effusion respectively. This excellent correlation identified high-risk cases that should have heart-lung machine kept on the stand-by during operation of peri-cardiectomy in event of iatrogenic cardiac chamber laceration. KeywordsPre-operative transthoracic echocardiography, pericarditis, correlation.
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6

Sen, Sujoita, Logan Hallee, and Chi Keung Lam. "The Potential of Gamma Secretase as a Therapeutic Target for Cardiac Diseases." Journal of Personalized Medicine 11, no. 12 (December 4, 2021): 1294. http://dx.doi.org/10.3390/jpm11121294.

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Heart diseases are some of the most common and pressing threats to human health worldwide. The American Heart Association and the National Institute of Health jointly work to annually update data on cardiac diseases. In 2018, 126.9 million Americans were reported as having some form of cardiac disorder, with an estimated direct and indirect total cost of USD 363.4 billion. This necessitates developing therapeutic interventions for heart diseases to improve human life expectancy and economic relief. In this review, we look into gamma-secretase as a potential therapeutic target for cardiac diseases. Gamma-secretase, an aspartyl protease enzyme, is responsible for the cleavage and activation of a number of substrates that are relevant to normal cardiac development and function as found in mutation studies. Some of these substrates are involved in downstream signaling processes and crosstalk with pathways relevant to heart diseases. Most of the substrates and signaling events we explored were found to be potentially beneficial to maintain cardiac function in diseased conditions. This review presents an updated overview of the current knowledge on gamma-secretase processing of cardiac-relevant substrates and seeks to understand if the modulation of gamma-secretase activity would be beneficial to combat cardiac diseases.
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7

Salgiya, Dr Nirali. "Correlation of Serum Cardiac Troponin-T with Chronic Kidney Disease." Journal of Medical Science And clinical Research 05, no. 06 (June 30, 2017): 24178–86. http://dx.doi.org/10.18535/jmscr/v5i6.222.

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8

C, Devadawson. "Fish Consumption and Cardio Vascular Diseases in Sri Lanka." International Journal of Science and Research (IJSR) 13, no. 3 (March 5, 2024): 1838–49. http://dx.doi.org/10.21275/sr24327151256.

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9

Romakina, V. V., I. V. Zhirov, S. N. Nasonova, A. V. Zaseeva, A. G. Kochetov, O. V. Liang, and S. N. Tereshchenko. "MicroRNAs as Biomarkers of Cardiovascular Diseases." Kardiologiia 17, no. 1 (2018): 66–71. http://dx.doi.org/10.18087/cardio.2018.1.10083.

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10

Colpaert, Robin M. W., and Martina Calore. "MicroRNAs in Cardiac Diseases." Cells 8, no. 7 (July 18, 2019): 737. http://dx.doi.org/10.3390/cells8070737.

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Since their discovery 20 years ago, microRNAs have been related to posttranscriptional regulation of gene expression in major cardiac physiological and pathological processes. We know now that cardiac muscle phenotypes are tightly regulated by multiple noncoding RNA species to maintain cardiac homeostasis. Upon stress or various pathological conditions, this class of non-coding RNAs has been found to modulate different cardiac pathological conditions, such as contractility, arrhythmia, myocardial infarction, hypertrophy, and inherited cardiomyopathies. This review summarizes and updates microRNAs playing a role in the different processes underlying the pathogenic phenotypes of cardiac muscle and highlights their potential role as disease biomarkers and therapeutic targets.
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11

HOQUE, M., A. C. SAXENA, REETU, M. B. GUGJOO, and D. BODH. "Cardiac diseases in dogs." Indian Journal of Animal Health 58, no. 01 (June 1, 2019): 01. http://dx.doi.org/10.36062/ijah.58.1.2019.01-20.

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12

Latif, Lubna, and Usman Javed Iqbal. "PREVALENCE OF CARDIAC DISEASES." Professional Medical Journal 22, no. 11 (November 10, 2015): 1443–48. http://dx.doi.org/10.29309/tpmj/2015.22.11.922.

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Objectives: The objective of this study was to find the prevalence of cardiacdisease among pregnant females and its impact on feto-maternal outcome. Study Design:Descriptive case series. Setting: Cardiology department Gulab Devi Chest Hospital LahoreDuration: April 2013 to April 2014. Patients & Methods: All pregnant females with cardiacdisease at any gestation with booked or un-booked statutes were included in this study. Patientswere admitted for thorough evaluation and investigations. Labor was monitored intensively. Dataregarding maternal outcomes were noted down on pre-formed questionnaire. Intra partum andpostpartum details were also noted down along with fetal outcome. The results were analyzedusing SPSS version 16.0.. Results: The total number of females presented with cardiac diseasewas 2650, out of which only 35 women were reported as pregnant. The duration of pregnancyat the time of presentation was as follows: 05 (14.2%) females presented in first trimester, 20(57.1%) in second trimester, 08 (22.8%) in third trimester and 02 (5.7%) patients presented inpostpartum period. There were 08 (22.8%) patients who had preterm labor. In terms of fetaloutcome 04 babies had birth weight of less than 1.5 kg, 12 had 1.5-2.0 kg, 15 were in rangeof 2-2.5 kg and 04 were more than 2.5 kg. 27 (77.1%) were term and 08 (22.8%) were pretermbabies. Cleft lip and atrial septal defect were the only two identified congenital anomalies.Conclusion: The overall prevalence of cardiac diseases during pregnancy was found to be1.3% in this study. Most common affected age group was of 20-25 years. Most common cardiacdisease found in our patient was mitral stenosis. 02 pregnancies ended in intrauterine fetaldeath. 08 babies were born preterm. Cleft lip and atrial septal defect were the only two identifiedcongenital anomalies in newborn delivered by our pregnant patients. Every effort should madeto create awareness regarding pre-pregnancy counseling, so that associated fetal and maternalmorbidity can be reduced.
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13

Kathuria, Sanjeev, Abhimanyu Uppal, Vimal Mehta, and Anunyay Gupta. "Cardiac Diseases and Obesity." Journal of Postgraduate Medicine, Education and Research 55, no. 1 (2021): 12–20. http://dx.doi.org/10.5005/jp-journals-10028-1423.

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14

McDermott, B., and D. Bell. "NPY and Cardiac Diseases." Current Topics in Medicinal Chemistry 7, no. 17 (September 1, 2007): 1692–703. http://dx.doi.org/10.2174/156802607782340939.

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15

Araub, Salman A. "INFLAMMATION AND CARDIAC DISEASES." Shock 21, no. 6 (June 2004): 579. http://dx.doi.org/10.1097/00024382-200406000-00015.

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16

Genton, Edward. "Anticoagulation in cardiac diseases." Postgraduate Medicine 77, no. 6 (May 1985): 109–16. http://dx.doi.org/10.1080/00325481.1985.11698984.

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17

Tansella, Michele. "Depression and cardiac diseases." Epidemiologia e Psichiatria Sociale 11, no. 2 (June 2002): 63–64. http://dx.doi.org/10.1017/s1121189x00005509.

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18

Duhig, Edwina. "Inflammation and Cardiac Diseases." Pathology 36, no. 6 (December 2004): 597. http://dx.doi.org/10.1016/s0031-3025(16)39696-9.

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19

Jarvis, Sheba, and Catherine Nelson-Piercy. "Cardiac diseases complicating pregnancy." Anaesthesia & Intensive Care Medicine 11, no. 8 (August 2010): 305–9. http://dx.doi.org/10.1016/j.mpaic.2010.04.015.

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20

Fayssoil, A. "Cardiac diseases in sarcoglycanopathies." International Journal of Cardiology 144, no. 1 (September 2010): 67–68. http://dx.doi.org/10.1016/j.ijcard.2008.12.048.

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21

Dhalla, Naranjan. "Role of Intracellular Ca2+-overload in Cardiac Dysfunction in Heart Disease." Clinical Cardiology and Cardiovascular Interventions 3, no. 2 (January 2, 2020): 01–10. http://dx.doi.org/10.31579/2641-0419/038.

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22

Belenkov, Y. N., E. V. Privalova, M. V. Kozhevnikova, E. O. Korobkova, I. S. Ilgisonis, V. Y. Kaplunova, G. A. SHakaryants, et al. "Metabolomic Profiling of Patients With Cardiovascular Diseases." Kardiologiia 17, no. 9 (2018): 59–62. http://dx.doi.org/10.18087/cardio.2018.9.10172.

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23

Christle, Jeffrey W., Steven G. Hershman, Jessica Torres Soto, and Euan A. Ashley. "Mobile Health Monitoring of Cardiac Status." Annual Review of Biomedical Data Science 3, no. 1 (July 20, 2020): 243–63. http://dx.doi.org/10.1146/annurev-biodatasci-030220-105124.

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Cardiovascular diseases (CVDs) are responsible for more deaths than any other cause, with coronary heart disease and stroke accounting for two-thirds of those deaths. Morbidity and mortality due to CVD are largely preventable, through either primary prevention of disease or secondary prevention of cardiac events. Monitoring cardiac status in healthy and diseased cardiovascular systems has the potential to dramatically reduce cardiac illness and injury. Smart technology in concert with mobile health platforms is creating an environment where timely prevention of and response to cardiac events are becoming a reality.
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24

Bykova, A. A., L. K. Malinovskaya, P. Sh Chomakhidze, O. V. Trushina, Y. R. Shaltaeva, V. V. Belyakov, A. V. Golovin, et al. "Exhaled Breath Analysis in Diagnostics of Cardiovascular Diseases." Kardiologiia 59, no. 7 (July 19, 2019): 61–67. http://dx.doi.org/10.18087/cardio.2019.7.10263.

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Exhaled breath analysis is a novel tool for diagnostics of different diseases. Taking into account the secretory function of the lungs, the composition of exhaled breath is different in physiological and pathological conditions. In this review we consider of some substances which content vary in cardiovascular diseases – pentane, isoprene, carbon monoxide and trimethylamine. Modern technologies allow to move the analysis of exhaled breath from research laboratories into clinical practice. Thus, a new tool for real time of screening various cardiovascular diseases has appeared in the arsenal of physicians.
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25

Sidorenko, B. A. Sidorenko. "R.G. Oganov, M.N. Mamedov «Handbook of Internal Diseases»." Kardiologiia 9_2016 (September 27, 2016): 67. http://dx.doi.org/10.18565/cardio.2016.9.67.

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26

Debbal, Sidi. "Cardiac Severity Analysis." Journal of Thoracic Disease and Cardiothoracic Surgery 2, no. 2 (August 11, 2021): 01–09. http://dx.doi.org/10.31579/2693-2156/023.

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Phonocardiogram (PCG) signal is a particular approach to explore cardiac activity, to develop technics that may serve medical staff to diagnose several cardiac diseases. We took advantage of PCG signal that shows heart murmurs on its tracing dissimilar to other cardiac signals, to design an algorithm to study and classify heart murmurs. In this paper, the importance is given to the severity of murmurs to highlight its impact, since depending on its stage the patient could be in life-threatening point; therefore, the purpose of this paper is focused on three essential steps: according to the algorithm, extracting murmurs and classifying them to deferent stages then investigate the impact of severity on cardiac frequency through some parameters. The severity stage calculation was based on energy ratio (ER) which is recommended by recent studies as an effective factor, however, we succeed to validate that murmur energy (ME) is also a qualified feature to determine severity. But despite that murmur duration, it's an inefficient way to judge the cardiac severity, which is a very important indicator of the general health of the human body. This study is done on considering many patients and it reveals very interesting results.
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27

Sharma, Vikas, Akhalesh kumar, Kartik Singhal, Chandana Majee, and Salahuddin. "Advancement in treating Cardiac Diseases using Cardiac Device." International Journal of PharmTech Research 13, no. 3 (2020): 217–22. http://dx.doi.org/10.20902/ijptr.2019.130312.

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From the origin of ancient Vedas or Shastras; there was an awareness of artificial intelligence but in different meanings. In present scenario, one has to perform a lot of research for the production of works relating with artificial intelligence. Basically, artificial intelligence is a huge group of skills from advanced machines used for finding the solutions of different fields i.e. in pharma fields or non-pharma fields. The problem of heart failure or heart attack is very big health issue which is assisted with more than 23 million peoples worldwide. Heart failure can be held due to the vasoconstriction or improper pumping mechanism of ventricles. Heart failure heart logic device is a new tsunami in the healthcare system for cardiac devices. This device is in two different forms which are as (ICD) implantable cardioverter defibrillator and other oneiscardiac resynchronization therapy defibrillator (CRT-D). Heart logic heart failure diagnostic device contains multiple sensors to track physiological functioning of the heart. There are Heart sound sensors which checks signs of elevated filling pressure and weakened ventricular contraction. There are also a sensor for checking pulmonary edema. Respiration sensor is used to monitor the rapid shallow breathing system which is associated with shortness of breath. Heart rate sensors check the heart rate and arrhythmia conditions. This device can predict heart failure events weeks before they happen. This artificial intelligence assisted device is showing the sensitivity in more than 70% of peoples to save the valuable lives of the human beings
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Cheng, Jianding, Wenzhao Wei, Ying Fang, Nan Zhou, Qiuping Wu, and Qianhao Zhao. "Sudden cardiac death and cardiac sodium channel diseases." Journal of Forensic Science and Medicine 8, no. 4 (2022): 179. http://dx.doi.org/10.4103/jfsm.jfsm_123_22.

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29

Méndez Eirín, Elizabet, Yago Suárez Ouréns, and José Luis Guerra Vázquez. "Cardiac manifestations of rheumatic diseases." Medicina Clínica (English Edition) 156, no. 12 (June 2021): 615–21. http://dx.doi.org/10.1016/j.medcle.2021.01.006.

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30

Dubois-Deruy, Emilie, Yara El Masri, Annie Turkieh, Philippe Amouyel, Florence Pinet, and Jean-Sébastien Annicotte. "Cardiac Acetylation in Metabolic Diseases." Biomedicines 10, no. 8 (July 29, 2022): 1834. http://dx.doi.org/10.3390/biomedicines10081834.

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Lysine acetylation is a highly conserved mechanism that affects several biological processes such as cell growth, metabolism, enzymatic activity, subcellular localization of proteins, gene transcription or chromatin structure. This post-translational modification, mainly regulated by lysine acetyltransferase (KAT) and lysine deacetylase (KDAC) enzymes, can occur on histone or non-histone proteins. Several studies have demonstrated that dysregulated acetylation is involved in cardiac dysfunction, associated with metabolic disorder or heart failure. Since the prevalence of obesity, type 2 diabetes or heart failure rises and represents a major cause of cardiovascular morbidity and mortality worldwide, cardiac acetylation may constitute a crucial pathway that could contribute to disease development. In this review, we summarize the mechanisms involved in the regulation of cardiac acetylation and its roles in physiological conditions. In addition, we highlight the effects of cardiac acetylation in physiopathology, with a focus on obesity, type 2 diabetes and heart failure. This review sheds light on the major role of acetylation in cardiovascular diseases and emphasizes KATs and KDACs as potential therapeutic targets for heart failure.
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Juhola, Martti, Henry Joutsijoki, Kirsi Penttinen, Disheet Shah, Risto-Pekka Pölönen, and Katriina Aalto-Setälä. "Data analytics for cardiac diseases." Computers in Biology and Medicine 142 (March 2022): 105218. http://dx.doi.org/10.1016/j.compbiomed.2022.105218.

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32

TOUMANIDIS, S. T., C. M. PAPAMICHAEL, L. G. ANTONIADES, M. I. PANTELIA, N. S. SARIDAKIS, M. E. MAVRIKAKIS, D. A. SIDERIS, and S. D. MOULOPOULOS. "Cardiac involvement in collagen diseases." European Heart Journal 16, no. 2 (February 1995): 257–62. http://dx.doi.org/10.1093/oxfordjournals.eurheartj.a060893.

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33

Schannwell, C. M., and B. E. Strauer. "Cardiac diseases of the elderly." DMW - Deutsche Medizinische Wochenschrift 130, no. 12 (March 2005): 693–97. http://dx.doi.org/10.1055/s-2005-865081.

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34

Komar, Monika. "Cardiac Tumours and Malignancy Diseases." Journal of Rare Cardiovascular Diseases 3, no. 6 (2018): 191. http://dx.doi.org/10.20418/jrcd.vol3no6.323.

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35

AMAUCHI, HIROSHI. "Cineangiographic Technique in Cardiac Diseases." Japanese Journal of Radiological Technology 53, no. 6 (1997): 708–13. http://dx.doi.org/10.6009/jjrt.kj00001355783.

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36

Gawałko, Monika, Paweł Balsam, Piotr Lodziński, Marcin Grabowski, Bartosz Krzowski, Grzegorz Opolski, and Jędrzej Kosiuk. "Cardiac Arrhythmias in Autoimmune Diseases." Circulation Journal 84, no. 5 (April 24, 2020): 685–94. http://dx.doi.org/10.1253/circj.cj-19-0705.

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37

Nunes, Maria Carmo P., Milton Henriques Guimarães Júnior, Adriana Costa Diamantino, Claudio Leo Gelape, and Teresa Cristina Abreu Ferrari. "Cardiac manifestations of parasitic diseases." Heart 103, no. 9 (March 11, 2017): 651–58. http://dx.doi.org/10.1136/heartjnl-2016-309870.

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38

Anan, Ryuichiro, Masanori Nakagawa, Masaaki Miyata, Itsuro Higuchi, Shoichiro Nakao, Masahito Suehara, Mitsuhiro Osame, and Hiromitsu Tanaka. "Cardiac Involvement in Mitochondrial Diseases." Circulation 91, no. 4 (February 15, 1995): 955–61. http://dx.doi.org/10.1161/01.cir.91.4.955.

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39

Pourmand, Rahman. "CARDIAC DYSFUNCTION IN NEUROMUSCULAR DISEASES." Neurologist 6, no. 2 (March 2000): 67–82. http://dx.doi.org/10.1097/00127893-200006020-00001.

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40

Maksimović, R., P. M. Seferović, A. D. Ristić, B. Vujisić-Tešić, D. S. Simeunović, G. Radovanović, M. Matucci-Cerinic, and B. Maisch. "Cardiac imaging in rheumatic diseases." Rheumatology 45, suppl_4 (October 2006): iv26—iv31. http://dx.doi.org/10.1093/rheumatology/kel309.

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Kuliev, Anver, Ekaterina Pomerantseva, Dana Polling, Oleg Verlinsky, and Svetlana Rechitsky. "PGD for inherited cardiac diseases." Reproductive BioMedicine Online 24, no. 4 (April 2012): 443–53. http://dx.doi.org/10.1016/j.rbmo.2011.12.009.

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42

Allen, Hugh D., Philip T. Thrush, Timothy M. Hoffman, Kevin M. Flanigan, and Jerry R. Mendell. "Cardiac Management in Neuromuscular Diseases." Physical Medicine and Rehabilitation Clinics of North America 23, no. 4 (November 2012): 855–68. http://dx.doi.org/10.1016/j.pmr.2012.08.001.

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43

Shimizu, Ippei, and Tohru Minamino. "Cellular senescence in cardiac diseases." Journal of Cardiology 74, no. 4 (October 2019): 313–19. http://dx.doi.org/10.1016/j.jjcc.2019.05.002.

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Daniels, Curt J., and Wayne H. Franklin. "COMMON CARDIAC DISEASES IN ADOLESCENTS." Pediatric Clinics of North America 44, no. 6 (December 1997): 1591–601. http://dx.doi.org/10.1016/s0031-3955(05)70576-9.

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Harris, Samantha P., and Pieter P. de Tombe. "Sarcomeric mutations in cardiac diseases." Pflügers Archiv - European Journal of Physiology 471, no. 5 (April 11, 2019): 659–60. http://dx.doi.org/10.1007/s00424-019-02275-2.

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46

Panteghini, Mauro. "Biochemical markers of cardiac diseases." Jugoslovenska medicinska biohemija 23, no. 3 (2004): 201–11. http://dx.doi.org/10.2298/jmh0403201p.

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This article reviews the current contribution of the determination of biochemical markers to clinical cardiology and discusses some important developments in this field. Biochemical markers play a pivotal role in the diagnosis and management of patients with acute coronary syndrome (ACS), as witnessed by the incorporation of cardiac troponins into new international guidelines for patients with ACS and in the redefinition of myocardial infarction. Despite the success of cardiac troponins, there is still a need for development of early markers that can reliably rule out ACS from the emergency room at presentation and detect myocardial ischemia also in the absence of irreversible myocyte injury. Under investigation are two classes of indicators: markers of early injury/ischemia and markers of coronary plaque instability and disruption. Finally, with the characterization of the cardiac natriuretic peptides, Laboratory Medicine is also assuming part in the assessment of cardiac function.
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Uzun Ozsahin, Dilber, Cemre Ozgocmen, Ozlem Balcioglu, Ilker Ozsahin, and Berna Uzun. "Diagnostic AI and Cardiac Diseases." Diagnostics 12, no. 12 (November 22, 2022): 2901. http://dx.doi.org/10.3390/diagnostics12122901.

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(1) Background: The purpose of this study is to review and highlight recent advances in diagnostic uses of artificial intelligence (AI) for cardiac diseases, in order to emphasize expected benefits to both patients and healthcare specialists; (2) Methods: We focused on four key search terms (Cardiac Disease, diagnosis, artificial intelligence, machine learning) across three different databases (Pubmed, European Heart Journal, Science Direct) between 2017–2022 in order to reach relatively more recent developments in the field. Our review was structured in order to clearly differentiate publications according to the disease they aim to diagnose (coronary artery disease, electrophysiological and structural heart diseases); (3) Results: Each study had different levels of success, where declared sensitivity, specificity, precision, accuracy, area under curve and F1 scores were reported for every article reviewed; (4) Conclusions: the number and quality of AI-assisted cardiac disease diagnosis publications will continue to increase through each year. We believe AI-based diagnosis should only be viewed as an additional tool assisting doctors’ own judgement, where the end goal is to provide better quality of healthcare and to make getting medical help more affordable and more accessible, for everyone, everywhere.
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48

Mateen, Farrah J., Diederik van de Beek, Walter K. Kremers, Richard C. Daly, Brooks S. Edwards, Christopher G. A. McGregor, and Eelco F. M. Wijdicks. "Neuromuscular Diseases After Cardiac Transplantation." Journal of Heart and Lung Transplantation 28, no. 3 (March 2009): 226–30. http://dx.doi.org/10.1016/j.healun.2008.12.004.

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49

Tseliou, E. "Cell therapy for cardiac diseases." Continuing Cardiology Education 3, no. 4 (December 2017): 170–75. http://dx.doi.org/10.1002/cce2.69.

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50

Li, WilliamA, and Yuchuan Ding. "Cardiac preconditioning and cardiovascular diseases." Heart and Mind 1, no. 1 (2017): 17. http://dx.doi.org/10.4103/hm.hm_4_17.

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